Run
4841008

Run 4841008

Task 3918 (Supervised Classification) pc1 Uploaded 08-07-2017 by Jan van Rijn
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  • openml-pimp openml-python Sklearn_0.18.1.
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Flow

sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.Conditiona lImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethres hold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classif ier=sklearn.svm.classes.SVC)(1)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(2)_axis0
openmlstudy14.preprocessing.ConditionalImputer(2)_categorical_features[]
openmlstudy14.preprocessing.ConditionalImputer(2)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(2)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(2)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy"median"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_verbose0
sklearn.preprocessing.data.OneHotEncoder(7)_categorical_features[]
sklearn.preprocessing.data.OneHotEncoder(7)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(7)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(7)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(7)_sparsefalse
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold0.0
sklearn.svm.classes.SVC(8)_C27.89352862288012
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.0
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma0.4425773025206858
sklearn.svm.classes.SVC(8)_kernel"rbf"
sklearn.svm.classes.SVC(8)_max_iter-1
sklearn.svm.classes.SVC(8)_probabilitytrue
sklearn.svm.classes.SVC(8)_random_state8495
sklearn.svm.classes.SVC(8)_shrinkingfalse
sklearn.svm.classes.SVC(8)_tol3.268043630912704e-05
sklearn.svm.classes.SVC(8)_verbosefalse

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

17 Evaluation measures

Area under ROC curve
0.6082 ± 0.102
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9141 ± 0.0191
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1993 ± 0.1819
Cross-validation details (10-fold Crossvalidation)
KB relative information score
92.9772 ± 13.0014
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1183 ± 0.0089
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1299 ± 0.0037
Cross-validation details (10-fold Crossvalidation)
Number of instances
1109
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9199 ± 0.0388
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9351 ± 0.0126
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.3667
Cross-validation details (10-fold Crossvalidation)
Recall
0.9351 ± 0.0126
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9107 ± 0.0651
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2542 ± 0.0073
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2451 ± 0.0204
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9641 ± 0.0788
Cross-validation details (10-fold Crossvalidation)